To combine the ideas of parametric and non-parametric style transfer Sheng et al. [1]} propose extending the WCT by performing nearest neighbor replacement of (whitened) content features with (whitened) style features in between the whitening and coloring steps. Zhang et al. [2]} proposes a different intermediate between non-parametric methods based on nearest neighbors and parametric methods assuming the distribution of style features is gaussian [3]}, [4]}. They propose modelling the distribution of style features as a mixture of gaussians, then using a graph cut to find the optimal matching between feature clusters. This allows a separate transformation to be applied to each cluster of content features.
